摘要
油性皮肤的护理是中国年轻女性普遍面临的问题之一。目前,皮肤类型的分析在很大程度上基于主观评估,文献中尚未报道基于无创性皮肤测试设备的油性皮肤分类标准。本研究基于箱形图数据分布和机器学习聚类算法,详细讨论了油性皮肤的无创、客观、定量分类方法,并与皮肤科医生经验值进行互相佐证对比。在此基础上,通过多功能探头测试仪和面部皮肤成像系统定量采集了皮肤屏障、色度、弹性、痤疮等指标数据,分析了油性皮肤的伴随特点和易感皮肤问题,明晰了中国年轻女性油性皮肤的特点,并评估了油性皮肤的痘、敏风险程度。结果显示,基于面部水油分布的箱形图分类法优于本研究中的其他两类方法,油性皮肤的伴随特点为屏障受损、肤色暗沉、弹性较差、痤疮和毛孔多,且痘肌的发生风险在油性皮肤中显著增高。
Oily skincare is one of the common problems confronting young Chinese females.Currently,skin type characterization is largely based on self-reports and qualitative assessments by dermatologists.Quantitative classification approach for oily skin totally based on the non-invasive skin measurement devices has not been reported in the literatures.In this study,based on box-plot data and machine learning clustering algorithms for 2000 Chinese female subjects(mean aged 25.90±2.61),non-invasive,objective,and quantitative classification approach for oily skin were initially established and compared with dermatologists’empirical results for mutual corroboration.On this basis,this study quantitatively collected data on skin barrier,chromaticity,elasticity,acne and other indicators through a multifunctional probe tester and a facial skin imaging system,analyzed the accompanying characteristics of oily skin and susceptible skin problems,clarified the characteristics of oily skin in young Chinese females,and evaluated the risk level of acne and sensitivity of oily skin,with a view to providing scientific care and guidance for Chinese young females with oily skin groups.The results show that the box-plot classification method based on facial hydro-oil distribution is superior to the other two types of methods.The accompanying characteristics of oily skin are poor barrier,dull complexion,less elasticity,more acne and pores.In addition,the risk of acne-prone skin is significantly higher in oily skin based on odds ratio.
作者
杨笑笑
颜欢
尹雅婷
易帆
Xiaoxiao Yang;Huan Yan;Yating Yin;Fan Yi(School of Chemical and Material Engineering,Beijing Technology and Business University,Beijing 100048,China;Beijing Bloomage Hyingc and Technology Co.,Ltd.,Beijing 102600,China)
出处
《日用化学工业(中英文)》
CAS
北大核心
2023年第12期1412-1420,共9页
China Surfactant Detergent & Cosmetics
基金
北京市教委一般科技项目(KM202010011009)
北京市优秀人才培养资助青年骨干个人项目(2018000020124G032)。
关键词
皮肤参数
易感问题
地域分布
风险程度
油性皮肤护理
skin parameters
susceptibility
geographical distribution
odds ratio
oily skincare